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Feedforward neural network

Known as: Feed-forward neural networks, Feedforward neural networks, Feedforward 
A feedforward neural network is an artificial neural network wherein connections between the units do not form a cycle. As such, it is different from… 
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Related topics

Related topics

38 relations
Activation functionArtificial intelligenceArtificial neural networkAutomatic differentiation

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2010
2010
Overfitting by PSO trained feedforward neural networks
The purpose of this paper is to investigate the overfitting behavior of particle swarm optimization (PSO) trained neural networks… 
2004
2004
A Feedforward Neural Network based on Multi-Valued Neurons
A feedforward neural network based on multi-valued neurons is considered in the paper. It is shown that using a traditional… 
Highly Cited
2001
Highly Cited
2001
Nonlinear Dynamical Systems: Feedforward Neural Network Perspectives
From the Publisher: This book deals with a specialized part of neural networks having applications in control, signal processing… 
Highly Cited
2001
Highly Cited
2001
High precision linear motor control via relay-tuning and iterative learning based on zero-phase filtering
In this paper, with a modest amount of modeling effort, a feedback-feedforward control structure is proposed for precision motion… 
2001
2001
A clustering approach to incremental learning for feedforward neural networks
The sensitivity analysis approach to incremental learning presented by Engelbrecht and Cloete (1999) is extended in this paper… 
Highly Cited
1998
Highly Cited
1998
Establishing impacts of the inputs in a feedforward neural network
Artificial neural network models are now being widely used in various areas of statistical research. Nevertheless, there is a… 
Highly Cited
1996
Highly Cited
1996
A time-domain feedback analysis of filtered-error adaptive gradient algorithms
This paper provides a time-domain feedback analysis of gradient-based adaptive schemes. A key emphasis is on the robustness… 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
1993
1993
Evolving Neural Feedforward Networks
For many practical problem domains the use of neural networks has led to very satisfactory results. Nevertheless the choice of an… 
Highly Cited
1988
Highly Cited
1988
Parallel architectures for artificial neural nets
The authors advocate digital VLSI architectures for implementing a wide variety of artificial neural nets (ANNs). A programmable… 
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